[{"date_updated":"2023-12-13T13:07:21Z","oa_version":"Published Version","year":"2023","date_published":"2023-09-25T00:00:00Z","has_accepted_license":"1","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"status":"public","day":"25","type":"journal_article","publisher":"Frontiers","ddc":["000"],"article_type":"original","doi":"10.3389/fmicb.2023.1257002","month":"09","title":"Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action","_id":"14449","citation":{"short":"D. D’Elia, J. Truu, L. Lahti, M. Berland, G. Papoutsoglou, M. Ceci, A. Zomer, M.B. Lopes, E. Ibrahimi, A. Gruca, A. Nechyporenko, M. Frohme, T. Klammsteiner, E.C.D.S. Pau, L.J. Marcos-Zambrano, K. Hron, G. Pio, A. Simeon, R. Suharoschi, I. Moreno-Indias, A. Temko, M. Nedyalkova, E.S. Apostol, C.O. Truică, R. Shigdel, J.H. Telalović, E. Bongcam-Rudloff, P. Przymus, N.B. Jordamović, L. Falquet, S. Tarazona, A. Sampri, G. Isola, D. Pérez-Serrano, V. Trajkovik, L. Klucar, T. Loncar-Turukalo, A.S. Havulinna, C. Jansen, R.J. Bertelsen, M.J. Claesson, Frontiers in Microbiology 14 (2023).","mla":"D’Elia, Domenica, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” <i>Frontiers in Microbiology</i>, vol. 14, 1257002, Frontiers, 2023, doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1257002\">10.3389/fmicb.2023.1257002</a>.","ieee":"D. D’Elia <i>et al.</i>, “Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action,” <i>Frontiers in Microbiology</i>, vol. 14. Frontiers, 2023.","apa":"D’Elia, D., Truu, J., Lahti, L., Berland, M., Papoutsoglou, G., Ceci, M., … Claesson, M. J. (2023). Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. <i>Frontiers in Microbiology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fmicb.2023.1257002\">https://doi.org/10.3389/fmicb.2023.1257002</a>","ama":"D’Elia D, Truu J, Lahti L, et al. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. <i>Frontiers in Microbiology</i>. 2023;14. doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1257002\">10.3389/fmicb.2023.1257002</a>","ista":"D’Elia D, Truu J, Lahti L, Berland M, Papoutsoglou G, Ceci M, Zomer A, Lopes MB, Ibrahimi E, Gruca A, Nechyporenko A, Frohme M, Klammsteiner T, Pau ECDS, Marcos-Zambrano LJ, Hron K, Pio G, Simeon A, Suharoschi R, Moreno-Indias I, Temko A, Nedyalkova M, Apostol ES, Truică CO, Shigdel R, Telalović JH, Bongcam-Rudloff E, Przymus P, Jordamović NB, Falquet L, Tarazona S, Sampri A, Isola G, Pérez-Serrano D, Trajkovik V, Klucar L, Loncar-Turukalo T, Havulinna AS, Jansen C, Bertelsen RJ, Claesson MJ. 2023. Advancing microbiome research with machine learning: Key findings from the ML4Microbiome COST action. Frontiers in Microbiology. 14, 1257002.","chicago":"D’Elia, Domenica, Jaak Truu, Leo Lahti, Magali Berland, Georgios Papoutsoglou, Michelangelo Ceci, Aldert Zomer, et al. “Advancing Microbiome Research with Machine Learning: Key Findings from the ML4Microbiome COST Action.” <i>Frontiers in Microbiology</i>. Frontiers, 2023. <a href=\"https://doi.org/10.3389/fmicb.2023.1257002\">https://doi.org/10.3389/fmicb.2023.1257002</a>."},"article_processing_charge":"Yes","isi":1,"intvolume":"        14","scopus_import":"1","file_date_updated":"2023-10-30T13:38:48Z","publication":"Frontiers in Microbiology","author":[{"first_name":"Domenica","full_name":"D’Elia, Domenica","last_name":"D’Elia"},{"first_name":"Jaak","full_name":"Truu, Jaak","last_name":"Truu"},{"last_name":"Lahti","full_name":"Lahti, Leo","first_name":"Leo"},{"last_name":"Berland","full_name":"Berland, Magali","first_name":"Magali"},{"full_name":"Papoutsoglou, Georgios","last_name":"Papoutsoglou","first_name":"Georgios"},{"last_name":"Ceci","full_name":"Ceci, Michelangelo","first_name":"Michelangelo"},{"first_name":"Aldert","last_name":"Zomer","full_name":"Zomer, Aldert"},{"first_name":"Marta B.","last_name":"Lopes","full_name":"Lopes, Marta B."},{"first_name":"Eliana","full_name":"Ibrahimi, Eliana","last_name":"Ibrahimi"},{"last_name":"Gruca","full_name":"Gruca, Aleksandra","first_name":"Aleksandra"},{"first_name":"Alina","full_name":"Nechyporenko, Alina","last_name":"Nechyporenko"},{"first_name":"Marcus","full_name":"Frohme, Marcus","last_name":"Frohme"},{"first_name":"Thomas","full_name":"Klammsteiner, Thomas","last_name":"Klammsteiner"},{"last_name":"Pau","full_name":"Pau, Enrique Carrillo De Santa","first_name":"Enrique Carrillo De Santa"},{"full_name":"Marcos-Zambrano, Laura Judith","last_name":"Marcos-Zambrano","first_name":"Laura Judith"},{"full_name":"Hron, Karel","last_name":"Hron","first_name":"Karel"},{"last_name":"Pio","full_name":"Pio, Gianvito","first_name":"Gianvito"},{"last_name":"Simeon","full_name":"Simeon, Andrea","first_name":"Andrea"},{"first_name":"Ramona","full_name":"Suharoschi, Ramona","last_name":"Suharoschi"},{"first_name":"Isabel","last_name":"Moreno-Indias","full_name":"Moreno-Indias, Isabel"},{"last_name":"Temko","full_name":"Temko, Andriy","first_name":"Andriy"},{"full_name":"Nedyalkova, Miroslava","last_name":"Nedyalkova","first_name":"Miroslava"},{"first_name":"Elena Simona","full_name":"Apostol, Elena Simona","last_name":"Apostol"},{"last_name":"Truică","full_name":"Truică, Ciprian Octavian","first_name":"Ciprian Octavian"},{"last_name":"Shigdel","full_name":"Shigdel, Rajesh","first_name":"Rajesh"},{"last_name":"Telalović","full_name":"Telalović, Jasminka Hasić","first_name":"Jasminka Hasić"},{"first_name":"Erik","last_name":"Bongcam-Rudloff","full_name":"Bongcam-Rudloff, Erik"},{"full_name":"Przymus, Piotr","last_name":"Przymus","first_name":"Piotr"},{"last_name":"Jordamović","full_name":"Jordamović, Naida Babić","first_name":"Naida Babić"},{"full_name":"Falquet, Laurent","last_name":"Falquet","first_name":"Laurent"},{"first_name":"Sonia","last_name":"Tarazona","full_name":"Tarazona, Sonia"},{"first_name":"Alexia","full_name":"Sampri, Alexia","last_name":"Sampri"},{"first_name":"Gaetano","last_name":"Isola","full_name":"Isola, Gaetano"},{"first_name":"David","last_name":"Pérez-Serrano","full_name":"Pérez-Serrano, David"},{"first_name":"Vladimir","last_name":"Trajkovik","full_name":"Trajkovik, Vladimir"},{"last_name":"Klucar","full_name":"Klucar, Lubos","first_name":"Lubos"},{"first_name":"Tatjana","full_name":"Loncar-Turukalo, Tatjana","last_name":"Loncar-Turukalo"},{"first_name":"Aki S.","last_name":"Havulinna","full_name":"Havulinna, Aki S."},{"first_name":"Christian","id":"837b2259-bcc9-11ed-a196-ae55927bc6e2","full_name":"Jansen, Christian","last_name":"Jansen"},{"first_name":"Randi J.","last_name":"Bertelsen","full_name":"Bertelsen, Randi J."},{"first_name":"Marcus Joakim","full_name":"Claesson, Marcus Joakim","last_name":"Claesson"}],"publication_identifier":{"eissn":["1664-302X"]},"oa":1,"pmid":1,"file":[{"file_size":505078,"creator":"dernst","file_name":"2023_FrontiersMicrobiology_DElia.pdf","file_id":"14471","date_created":"2023-10-30T13:38:48Z","date_updated":"2023-10-30T13:38:48Z","content_type":"application/pdf","checksum":"6c0acdd8fa111a699826957b8dff19d5","success":1,"access_level":"open_access","relation":"main_file"}],"acknowledgement":"This study is based upon work from COST Action ML4Microbiome “Statistical and machine learning techniques in human microbiome studies” (CA18131), supported by COST (European Cooperation in Science and Technology), www.cost.eu. MB acknowledges support through the Metagenopolis grant ANR-11-DPBS-0001. IM-I acknowledges support by the “Miguel Servet Type II” program (CPII21/00013) of the ISCIII-Madrid (Spain), co-financed by the FEDER.\r\nThe authors are grateful to all COST Action CA18131 “Statistical and machine learning techniques in human microbiome studies” members for their contribution to the COST Action objectives, and to COST (European Cooperation in Science and Technology) for the economic support, www.cost.eu. WG2 and WG3 thank Emmanuelle Le Chatelier and Pauline Barbet (Université Paris-Saclay, INRAE, MetaGenoPolis, 78350, Jouy-en-Josas, France) for preparing the shotgun CRC benchmark dataset.","publication_status":"published","language":[{"iso":"eng"}],"date_created":"2023-10-22T22:01:16Z","department":[{"_id":"ScienComp"}],"external_id":{"isi":["001080536000001"],"pmid":["37808321"]},"quality_controlled":"1","volume":14,"article_number":"1257002","abstract":[{"text":"The rapid development of machine learning (ML) techniques has opened up the data-dense field of microbiome research for novel therapeutic, diagnostic, and prognostic applications targeting a wide range of disorders, which could substantially improve healthcare practices in the era of precision medicine. However, several challenges must be addressed to exploit the benefits of ML in this field fully. In particular, there is a need to establish “gold standard” protocols for conducting ML analysis experiments and improve interactions between microbiome researchers and ML experts. The Machine Learning Techniques in Human Microbiome Studies (ML4Microbiome) COST Action CA18131 is a European network established in 2019 to promote collaboration between discovery-oriented microbiome researchers and data-driven ML experts to optimize and standardize ML approaches for microbiome analysis. This perspective paper presents the key achievements of ML4Microbiome, which include identifying predictive and discriminatory ‘omics’ features, improving repeatability and comparability, developing automation procedures, and defining priority areas for the novel development of ML methods targeting the microbiome. The insights gained from ML4Microbiome will help to maximize the potential of ML in microbiome research and pave the way for new and improved healthcare practices.","lang":"eng"}],"license":"https://creativecommons.org/licenses/by/4.0/"},{"corr_author":"1","language":[{"iso":"eng"}],"external_id":{"pmid":["37007485"],"isi":["000961542100001"]},"department":[{"_id":"SyCr"}],"date_created":"2023-01-31T08:13:40Z","publication_status":"published","abstract":[{"lang":"eng","text":"Hosts can carry many viruses in their bodies, but not all of them cause disease. We studied ants as a social host to determine both their overall viral repertoire and the subset of actively infecting viruses across natural populations of three subfamilies: the Argentine ant (Linepithema humile, Dolichoderinae), the invasive garden ant (Lasius neglectus, Formicinae) and the red ant (Myrmica rubra, Myrmicinae). We used a dual sequencing strategy to reconstruct complete virus genomes by RNA-seq and to simultaneously determine the small interfering RNAs (siRNAs) by small RNA sequencing (sRNA-seq), which constitute the host antiviral RNAi immune response. This approach led to the discovery of 41 novel viruses in ants and revealed a host ant-specific RNAi response (21 vs. 22 nt siRNAs) in the different ant species. The efficiency of the RNAi response (sRNA/RNA read count ratio) depended on the virus and the respective ant species, but not its population. Overall, we found the highest virus abundance and diversity per population in Li. humile, followed by La. neglectus and M. rubra. Argentine ants also shared a high proportion of viruses between populations, whilst overlap was nearly absent in M. rubra. Only one of the 59 viruses was found to infect two of the ant species as hosts, revealing high host-specificity in active infections. In contrast, six viruses actively infected one ant species, but were found as contaminants only in the others. Disentangling spillover of disease-causing infection from non-infecting contamination across species is providing relevant information for disease ecology and ecosystem management."}],"article_number":"1119002","quality_controlled":"1","volume":14,"intvolume":"        14","isi":1,"publication":"Frontiers in Microbiology","scopus_import":"1","file_date_updated":"2023-04-17T07:49:09Z","author":[{"last_name":"Viljakainen","full_name":"Viljakainen, Lumi","first_name":"Lumi"},{"orcid":"0000-0002-3712-925X","id":"393B1196-F248-11E8-B48F-1D18A9856A87","first_name":"Matthias","last_name":"Fürst","full_name":"Fürst, Matthias"},{"last_name":"Grasse","full_name":"Grasse, Anna V","id":"406F989C-F248-11E8-B48F-1D18A9856A87","first_name":"Anna V"},{"last_name":"Jurvansuu","full_name":"Jurvansuu, Jaana","first_name":"Jaana"},{"id":"403169A4-080F-11EA-9993-BF3F3DDC885E","first_name":"Jinook","full_name":"Oh, Jinook","last_name":"Oh","orcid":"0000-0001-7425-2372"},{"last_name":"Tolonen","full_name":"Tolonen, Lassi","first_name":"Lassi"},{"first_name":"Thomas","last_name":"Eder","full_name":"Eder, Thomas"},{"first_name":"Thomas","last_name":"Rattei","full_name":"Rattei, Thomas"},{"first_name":"Sylvia","id":"2F64EC8C-F248-11E8-B48F-1D18A9856A87","full_name":"Cremer, Sylvia","last_name":"Cremer","orcid":"0000-0002-2193-3868"}],"oa":1,"publication_identifier":{"eissn":["1664-302X"]},"file":[{"success":1,"relation":"main_file","access_level":"open_access","file_id":"12843","date_created":"2023-04-17T07:49:09Z","file_name":"2023_FrontMicrobiology_Viljakainen.pdf","creator":"dernst","file_size":4866332,"content_type":"application/pdf","checksum":"cd52292963acce1111634d9fac08c699","date_updated":"2023-04-17T07:49:09Z"}],"acknowledgement":"We thank D.J. Obbard for sharing the details of the dual RNA-seq/sRNA-seq approach, S.\r\nMetzler and R. Ferrigato for the photographs (Figure 1), M. Konrad, B. Casillas-Perez, C.D.\r\nPull and X. Espadaler for help with ant collection, and the Social Immunity Team at IST\r\nAustria, in particular J. Robb, A. Franschitz, E. Naderlinger, E. Dawson and B. Casillas-Perez\r\nfor support and comments on the manuscript. The study was funded by the Austrian Science\r\nFund (FWF; M02076-B25 to MAF) and the Academy of Finland (343022 to LV). ","pmid":1,"doi":"10.3389/fmicb.2023.1119002","article_type":"original","ddc":["570"],"citation":{"short":"L. Viljakainen, M. Fürst, A.V. Grasse, J. Jurvansuu, J. Oh, L. Tolonen, T. Eder, T. Rattei, S. Cremer, Frontiers in Microbiology 14 (2023).","mla":"Viljakainen, Lumi, et al. “Antiviral Immune Response Reveals Host-Specific Virus Infections in Natural Ant Populations.” <i>Frontiers in Microbiology</i>, vol. 14, 1119002, Frontiers, 2023, doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1119002\">10.3389/fmicb.2023.1119002</a>.","ieee":"L. Viljakainen <i>et al.</i>, “Antiviral immune response reveals host-specific virus infections in natural ant populations,” <i>Frontiers in Microbiology</i>, vol. 14. Frontiers, 2023.","ama":"Viljakainen L, Fürst M, Grasse AV, et al. Antiviral immune response reveals host-specific virus infections in natural ant populations. <i>Frontiers in Microbiology</i>. 2023;14. doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1119002\">10.3389/fmicb.2023.1119002</a>","apa":"Viljakainen, L., Fürst, M., Grasse, A. V., Jurvansuu, J., Oh, J., Tolonen, L., … Cremer, S. (2023). Antiviral immune response reveals host-specific virus infections in natural ant populations. <i>Frontiers in Microbiology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fmicb.2023.1119002\">https://doi.org/10.3389/fmicb.2023.1119002</a>","chicago":"Viljakainen, Lumi, Matthias Fürst, Anna V Grasse, Jaana Jurvansuu, Jinook Oh, Lassi Tolonen, Thomas Eder, Thomas Rattei, and Sylvia Cremer. “Antiviral Immune Response Reveals Host-Specific Virus Infections in Natural Ant Populations.” <i>Frontiers in Microbiology</i>. Frontiers, 2023. <a href=\"https://doi.org/10.3389/fmicb.2023.1119002\">https://doi.org/10.3389/fmicb.2023.1119002</a>.","ista":"Viljakainen L, Fürst M, Grasse AV, Jurvansuu J, Oh J, Tolonen L, Eder T, Rattei T, Cremer S. 2023. Antiviral immune response reveals host-specific virus infections in natural ant populations. Frontiers in Microbiology. 14, 1119002."},"article_processing_charge":"Yes (via OA deal)","title":"Antiviral immune response reveals host-specific virus infections in natural ant populations","month":"03","_id":"12469","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","oa_version":"Published Version","year":"2023","date_updated":"2025-04-23T08:54:27Z","date_published":"2023-03-16T00:00:00Z","project":[{"_id":"25DF61D8-B435-11E9-9278-68D0E5697425","grant_number":"M02076","call_identifier":"FWF","name":"Viral pathogens and social immunity in ants"}],"has_accepted_license":"1","publisher":"Frontiers","day":"16","type":"journal_article","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"status":"public"},{"has_accepted_license":"1","date_published":"2023-06-20T00:00:00Z","date_updated":"2024-10-09T21:03:59Z","oa_version":"Published Version","year":"2023","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","status":"public","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"day":"20","type":"journal_article","publisher":"Frontiers","ddc":["570"],"article_type":"original","doi":"10.3389/fmicb.2023.1049255","_id":"12478","month":"06","title":"Monitoring lineages of growing and dividing bacteria reveals an inducible memory of <i>mar</i> operon expression","article_processing_charge":"Yes","citation":{"chicago":"Guet, Calin C, L Bruneaux, P Oikonomou, M Aldana, and P Cluzel. “Monitoring Lineages of Growing and Dividing Bacteria Reveals an Inducible Memory of <i>Mar</i> Operon Expression.” <i>Frontiers in Microbiology</i>. Frontiers, 2023. <a href=\"https://doi.org/10.3389/fmicb.2023.1049255\">https://doi.org/10.3389/fmicb.2023.1049255</a>.","ista":"Guet CC, Bruneaux L, Oikonomou P, Aldana M, Cluzel P. 2023. Monitoring lineages of growing and dividing bacteria reveals an inducible memory of <i>mar</i> operon expression. Frontiers in Microbiology. 14, 1049255.","ama":"Guet CC, Bruneaux L, Oikonomou P, Aldana M, Cluzel P. Monitoring lineages of growing and dividing bacteria reveals an inducible memory of <i>mar</i> operon expression. <i>Frontiers in Microbiology</i>. 2023;14. doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1049255\">10.3389/fmicb.2023.1049255</a>","apa":"Guet, C. C., Bruneaux, L., Oikonomou, P., Aldana, M., &#38; Cluzel, P. (2023). Monitoring lineages of growing and dividing bacteria reveals an inducible memory of <i>mar</i> operon expression. <i>Frontiers in Microbiology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fmicb.2023.1049255\">https://doi.org/10.3389/fmicb.2023.1049255</a>","ieee":"C. C. Guet, L. Bruneaux, P. Oikonomou, M. Aldana, and P. Cluzel, “Monitoring lineages of growing and dividing bacteria reveals an inducible memory of <i>mar</i> operon expression,” <i>Frontiers in Microbiology</i>, vol. 14. Frontiers, 2023.","short":"C.C. Guet, L. Bruneaux, P. Oikonomou, M. Aldana, P. Cluzel, Frontiers in Microbiology 14 (2023).","mla":"Guet, Calin C., et al. “Monitoring Lineages of Growing and Dividing Bacteria Reveals an Inducible Memory of <i>Mar</i> Operon Expression.” <i>Frontiers in Microbiology</i>, vol. 14, 1049255, Frontiers, 2023, doi:<a href=\"https://doi.org/10.3389/fmicb.2023.1049255\">10.3389/fmicb.2023.1049255</a>."},"scopus_import":"1","author":[{"orcid":"0000-0001-6220-2052","last_name":"Guet","full_name":"Guet, Calin C","first_name":"Calin C","id":"47F8433E-F248-11E8-B48F-1D18A9856A87"},{"first_name":"L","last_name":"Bruneaux","full_name":"Bruneaux, L"},{"first_name":"P","full_name":"Oikonomou, P","last_name":"Oikonomou"},{"first_name":"M","full_name":"Aldana, M","last_name":"Aldana"},{"full_name":"Cluzel, P","last_name":"Cluzel","first_name":"P"}],"file_date_updated":"2023-07-31T07:16:34Z","publication":"Frontiers in Microbiology","intvolume":"        14","isi":1,"pmid":1,"acknowledgement":"This work was supported by NIH P50 award P50GM081892-02 to the University of Chicago, a catalyst grant from the Chicago Biomedical Consortium with support from The Searle Funds at The Chicago Community Trust to PC, and a Yen Fellowship to CCG. MA was partially supported by PAPIIT-UNAM grant IN-11322.","file":[{"creator":"dernst","file_name":"2023_FrontiersMicrobiology_Guet.pdf","date_created":"2023-07-31T07:16:34Z","file_id":"13322","file_size":6452841,"content_type":"application/pdf","checksum":"7dd322347512afaa5daf72a0154f2f07","date_updated":"2023-07-31T07:16:34Z","success":1,"access_level":"open_access","relation":"main_file"}],"oa":1,"publication_identifier":{"eissn":["1664-302X"]},"publication_status":"published","date_created":"2023-02-02T08:13:28Z","department":[{"_id":"CaGu"}],"external_id":{"pmid":["37485524"],"isi":["001030002600001"]},"corr_author":"1","language":[{"iso":"eng"}],"volume":14,"quality_controlled":"1","article_number":"1049255","abstract":[{"text":"In Gram negative bacteria, the multiple antibiotic resistance or mar operon, is known to control the expression of multi-drug efflux genes that protect bacteria from a wide range of drugs. As many different chemical compounds can induce this operon, identifying the parameters that govern the dynamics of its induction is crucial to better characterize the processes of tolerance and resistance. Most experiments have assumed that the properties of the mar transcriptional network can be inferred from population measurements. However, measurements from an asynchronous population of cells can mask underlying phenotypic variations of single cells. We monitored the activity of the mar promoter in single Escherichia coli cells in linear micro-colonies and established that the response to a steady level of inducer was most heterogeneous within individual colonies for an intermediate value of inducer. Specifically, sub-lineages defined by contiguous daughter-cells exhibited similar promoter activity, whereas activity was greatly variable between different sub-lineages. Specific sub-trees of uniform promoter activity persisted over several generations. Statistical analyses of the lineages suggest that the presence of these sub-trees is the signature of an inducible memory of the promoter state that is transmitted from mother to daughter cells. This single-cell study reveals that the degree of epigenetic inheritance changes as a function of inducer concentration, suggesting that phenotypic inheritance may be an inducible phenotype.","lang":"eng"}]},{"scopus_import":"1","author":[{"full_name":"Qi, Qin","last_name":"Qi","first_name":"Qin","id":"3B22D412-F248-11E8-B48F-1D18A9856A87","orcid":"0000-0002-6148-2416"},{"last_name":"Angermayr","full_name":"Angermayr, S. Andreas","first_name":"S. Andreas"},{"orcid":"0000-0003-4398-476X","full_name":"Bollenbach, Mark Tobias","last_name":"Bollenbach","first_name":"Mark Tobias","id":"3E6DB97A-F248-11E8-B48F-1D18A9856A87"}],"publication":"Frontiers in Microbiology","keyword":["microbiology"],"file_date_updated":"2021-11-11T10:54:40Z","intvolume":"        12","isi":1,"ec_funded":1,"pmid":1,"acknowledgement":"High-throughput sequencing data were generated by the Vienna BioCenter Core Facilities. The authors would like to thank Karin Mitosch, Bor Kavcic, and Nadine Kraupner for their constructive feedback. The authors would also like to thank Gertraud Stift, Julia Flor, Renate Srsek, Agnieszka Wiktor, and Booshini Fernando for technical support.","file":[{"success":1,"access_level":"open_access","relation":"main_file","creator":"cchlebak","file_name":"2021_FrontiersMicrob_Qi.pdf","file_id":"10272","date_created":"2021-11-11T10:54:40Z","file_size":2397203,"checksum":"d41321748e9588dd3cf03e9a7222127f","content_type":"application/pdf","date_updated":"2021-11-11T10:54:40Z"}],"publication_identifier":{"eissn":["1664-302X"]},"oa":1,"date_created":"2021-11-11T10:39:37Z","external_id":{"pmid":["34745067"],"isi":["000715997300001"]},"language":[{"iso":"eng"}],"publication_status":"published","article_number":"760017","abstract":[{"lang":"eng","text":"Understanding interactions between antibiotics used in combination is an important theme in microbiology. Using the interactions between the antifolate drug trimethoprim and the ribosome-targeting antibiotic erythromycin in Escherichia coli as a model, we applied a transcriptomic approach for dissecting interactions between two antibiotics with different modes of action. When trimethoprim and erythromycin were combined, the transcriptional response of genes from the sulfate reduction pathway deviated from the dominant effect of trimethoprim on the transcriptome. We successfully altered the drug interaction from additivity to suppression by increasing the sulfate level in the growth environment and identified sulfate reduction as an important metabolic determinant that shapes the interaction between the two drugs. Our work highlights the potential of using prioritization of gene expression patterns as a tool for identifying key metabolic determinants that shape drug-drug interactions. We further demonstrated that the sigma factor-binding protein gene crl shapes the interactions between the two antibiotics, which provides a rare example of how naturally occurring variations between strains of the same bacterial species can sometimes generate very different drug interactions."}],"volume":12,"quality_controlled":"1","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","date_published":"2021-10-20T00:00:00Z","has_accepted_license":"1","project":[{"name":"Revealing the mechanisms underlying drug interactions","call_identifier":"FWF","_id":"25E9AF9E-B435-11E9-9278-68D0E5697425","grant_number":"P27201-B22"},{"grant_number":"303507","_id":"25E83C2C-B435-11E9-9278-68D0E5697425","name":"Optimality principles in responses to antibiotics","call_identifier":"FP7"}],"date_updated":"2025-04-14T09:40:44Z","oa_version":"Published Version","year":"2021","day":"20","type":"journal_article","publisher":"Frontiers","status":"public","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"article_type":"original","doi":"10.3389/fmicb.2021.760017","ddc":["610"],"article_processing_charge":"No","citation":{"short":"Q. Qi, S.A. Angermayr, M.T. Bollenbach, Frontiers in Microbiology 12 (2021).","mla":"Qi, Qin, et al. “Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia Coli.” <i>Frontiers in Microbiology</i>, vol. 12, 760017, Frontiers, 2021, doi:<a href=\"https://doi.org/10.3389/fmicb.2021.760017\">10.3389/fmicb.2021.760017</a>.","ieee":"Q. Qi, S. A. Angermayr, and M. T. Bollenbach, “Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli,” <i>Frontiers in Microbiology</i>, vol. 12. Frontiers, 2021.","apa":"Qi, Q., Angermayr, S. A., &#38; Bollenbach, M. T. (2021). Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli. <i>Frontiers in Microbiology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fmicb.2021.760017\">https://doi.org/10.3389/fmicb.2021.760017</a>","ama":"Qi Q, Angermayr SA, Bollenbach MT. Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli. <i>Frontiers in Microbiology</i>. 2021;12. doi:<a href=\"https://doi.org/10.3389/fmicb.2021.760017\">10.3389/fmicb.2021.760017</a>","ista":"Qi Q, Angermayr SA, Bollenbach MT. 2021. Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli. Frontiers in Microbiology. 12, 760017.","chicago":"Qi, Qin, S. Andreas Angermayr, and Mark Tobias Bollenbach. “Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia Coli.” <i>Frontiers in Microbiology</i>. Frontiers, 2021. <a href=\"https://doi.org/10.3389/fmicb.2021.760017\">https://doi.org/10.3389/fmicb.2021.760017</a>."},"_id":"10271","month":"10","title":"Uncovering Key Metabolic Determinants of the Drug Interactions Between Trimethoprim and Erythromycin in Escherichia coli"},{"publication_status":"published","date_created":"2021-05-09T22:01:38Z","department":[{"_id":"FyKo"}],"external_id":{"isi":["000643713300001"]},"corr_author":"1","language":[{"iso":"eng"}],"volume":12,"quality_controlled":"1","article_number":"628622","abstract":[{"lang":"eng","text":"Shigella are pathogens originating within the Escherichia lineage but frequently classified as a separate genus. Shigella genomes contain numerous insertion sequences (ISs) that lead to pseudogenisation of affected genes and an increase of non-homologous recombination. Here, we study 414 genomes of E. coli and Shigella strains to assess the contribution of genomic rearrangements to Shigella evolution. We found that Shigella experienced exceptionally high rates of intragenomic rearrangements and had a decreased rate of homologous recombination compared to pathogenic and non-pathogenic E. coli. The high rearrangement rate resulted in independent disruption of syntenic regions and parallel rearrangements in different Shigella lineages. Specifically, we identified two types of chromosomally encoded E3 ubiquitin-protein ligases acquired independently by all Shigella strains that also showed a high level of sequence conservation in the promoter and further in the 5′-intergenic region. In the only available enteroinvasive E. coli (EIEC) strain, which is a pathogenic E. coli with a phenotype intermediate between Shigella and non-pathogenic E. coli, we found a rate of genome rearrangements comparable to those in other E. coli and no functional copies of the two Shigella-specific E3 ubiquitin ligases. These data indicate that the accumulation of ISs influenced many aspects of genome evolution and played an important role in the evolution of intracellular pathogens. Our research demonstrates the power of comparative genomics-based on synteny block composition and an important role of non-coding regions in the evolution of genomic islands."}],"scopus_import":"1","author":[{"full_name":"Seferbekova, Zaira","last_name":"Seferbekova","first_name":"Zaira"},{"first_name":"Alexey","full_name":"Zabelkin, Alexey","last_name":"Zabelkin"},{"last_name":"Yakovleva","full_name":"Yakovleva, Yulia","first_name":"Yulia"},{"first_name":"Robert","last_name":"Afasizhev","full_name":"Afasizhev, Robert"},{"full_name":"Dranenko, Natalia O.","last_name":"Dranenko","first_name":"Natalia O."},{"first_name":"Nikita","full_name":"Alexeev, Nikita","last_name":"Alexeev"},{"full_name":"Gelfand, Mikhail S.","last_name":"Gelfand","first_name":"Mikhail S."},{"id":"C4558D3C-6102-11E9-A62E-F418E6697425","first_name":"Olga","last_name":"Bochkareva","full_name":"Bochkareva, Olga","orcid":"0000-0003-1006-6639"}],"file_date_updated":"2021-05-11T13:05:52Z","publication":"Frontiers in Microbiology","isi":1,"intvolume":"        12","ec_funded":1,"acknowledgement":"We thank Fyodor Kondrashov for valuable advice and manuscript proofreading. We also thank Alla Mikheenko for assistance with Circos.","file":[{"access_level":"open_access","relation":"main_file","success":1,"date_updated":"2021-05-11T13:05:52Z","checksum":"2f856543add59273a482a7f326fc0400","content_type":"application/pdf","file_size":14362316,"file_name":"2021_Frontiers_Microbiology_Seferbekova.pdf","creator":"kschuh","date_created":"2021-05-11T13:05:52Z","file_id":"9384"}],"oa":1,"publication_identifier":{"eissn":["1664-302X"]},"ddc":["570"],"article_type":"original","doi":"10.3389/fmicb.2021.628622","_id":"9380","month":"04","title":"High rates of genome rearrangements and pathogenicity of Shigella spp","article_processing_charge":"No","citation":{"ama":"Seferbekova Z, Zabelkin A, Yakovleva Y, et al. High rates of genome rearrangements and pathogenicity of Shigella spp. <i>Frontiers in Microbiology</i>. 2021;12. doi:<a href=\"https://doi.org/10.3389/fmicb.2021.628622\">10.3389/fmicb.2021.628622</a>","apa":"Seferbekova, Z., Zabelkin, A., Yakovleva, Y., Afasizhev, R., Dranenko, N. O., Alexeev, N., … Bochkareva, O. (2021). High rates of genome rearrangements and pathogenicity of Shigella spp. <i>Frontiers in Microbiology</i>. Frontiers. <a href=\"https://doi.org/10.3389/fmicb.2021.628622\">https://doi.org/10.3389/fmicb.2021.628622</a>","chicago":"Seferbekova, Zaira, Alexey Zabelkin, Yulia Yakovleva, Robert Afasizhev, Natalia O. Dranenko, Nikita Alexeev, Mikhail S. Gelfand, and Olga Bochkareva. “High Rates of Genome Rearrangements and Pathogenicity of Shigella Spp.” <i>Frontiers in Microbiology</i>. Frontiers, 2021. <a href=\"https://doi.org/10.3389/fmicb.2021.628622\">https://doi.org/10.3389/fmicb.2021.628622</a>.","ista":"Seferbekova Z, Zabelkin A, Yakovleva Y, Afasizhev R, Dranenko NO, Alexeev N, Gelfand MS, Bochkareva O. 2021. High rates of genome rearrangements and pathogenicity of Shigella spp. Frontiers in Microbiology. 12, 628622.","short":"Z. Seferbekova, A. Zabelkin, Y. Yakovleva, R. Afasizhev, N.O. Dranenko, N. Alexeev, M.S. Gelfand, O. Bochkareva, Frontiers in Microbiology 12 (2021).","mla":"Seferbekova, Zaira, et al. “High Rates of Genome Rearrangements and Pathogenicity of Shigella Spp.” <i>Frontiers in Microbiology</i>, vol. 12, 628622, Frontiers, 2021, doi:<a href=\"https://doi.org/10.3389/fmicb.2021.628622\">10.3389/fmicb.2021.628622</a>.","ieee":"Z. Seferbekova <i>et al.</i>, “High rates of genome rearrangements and pathogenicity of Shigella spp,” <i>Frontiers in Microbiology</i>, vol. 12. Frontiers, 2021."},"has_accepted_license":"1","date_published":"2021-04-12T00:00:00Z","project":[{"grant_number":"754411","_id":"260C2330-B435-11E9-9278-68D0E5697425","call_identifier":"H2020","name":"ISTplus - Postdoctoral Fellowships"}],"date_updated":"2025-04-14T07:43:52Z","year":"2021","oa_version":"Published Version","user_id":"4359f0d1-fa6c-11eb-b949-802e58b17ae8","status":"public","tmp":{"short":"CC BY (4.0)","legal_code_url":"https://creativecommons.org/licenses/by/4.0/legalcode","image":"/images/cc_by.png","name":"Creative Commons Attribution 4.0 International Public License (CC-BY 4.0)"},"day":"12","type":"journal_article","publisher":"Frontiers"}]